Department of Chemical Engineering

Indian Institute of Technology Bombay

Spring Semester 2008-2009

CL 662:  Introduction to Computational Biology

 

Instructor:     Prof. P. Wangikar, Department of Chemical Eng.  

Contact:        022-2576 7232 or pramodw@iitb.ac.in 

Lectures:      Slot # 13 (Monday and Thursday 6:30-8:00 PM), KReSIT Seminar Hall, 3rd Floor.  (The course is also being offered through CDEEP)

 

Note:  There will be no lecture on 5/1/09 as I will be out of station.

 

Course Objective:  With greater throughput rates, industrial R&D laboratories are generating increasingly larger amounts of data on biological sequences, structures, properties, characteristics and time course experiments. As a result, today's researcher needs to be equipped with computational-biology tools to glean knowledge from this vast amount of data. This theory-cum-hands-on bioinformatics course introduces YOU to algorithms and tools for analyzing and comparing biological data, inter- and intra- database relationships and various algorithms. While the course is software-independent, the assignments will be solved using certain freely available bioinformatics software packages as well as Matlab.  Prior knowledge of programming is not necessary.  However, working knowledge of molecular biology and statistics would be useful.

 

Topics to be covered:

  1. Overview of biological systems, Internet resources for biological data
  2. Primer on Data mining, Classification and Clustering
  3. Gene Prediction Algorithms
  4. Sequence Analysis: Alignment, Sequence Profiles, Hidden Markov Model.
  5. Functional Genomics
  6. Protein 3-Dimensional Structure Analysis
  7. Gene Expression Data Analysis
  8. Student Project Presentations

 

Course Project: Groups of two (preferably one student with bio background  and one without bio-background), would undertake large-scale data-mining with a biological objective in mind.  The project theme can be identified by students or selected by discussion with the instructor.  The required databases and tools are to be identified by the students.  

 

Project Deadlines and weightage:

February 9, 2009 (15%):      Submission of title, abstract and 2-3 references (Max. one page)

March 2, 2009 (15%):           Mid-term, 5 min presentation in class (use upto 5 slides) —Discuss your progress.

April 2, 2009 (35%):             Final Project report due (Max. 10 pages; No appendix; Should include abstract, introduction, results and discussion, references)

April 6 and 9, 2009 (35%):  Final Project presentation in class. 

Grading Scheme:

            Exams:                       30%

            Assignments:             30%

            Project:                       30%

            Class Participation   10%

 

 

Reference books:

  1. D. W. Mount (2004) “Bioinformatics:  Sequence and Genome Analysis” 2nd edition, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY.
  2. A.D. Baxevanis and B.F.F. Ouellette (editors) (2001) “Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins” 2nd edition. John Wiley & Sons Inc. New York
  3. Creighton, T. E.  “Proteins Structures and Molecular Principles” W.H. Freeman
  4. Baldi, P. and Brunak, S. 2001 “Bioinformatics: The Machine Learning Approach” 2nd edition., MIT Press, Cambridge, MA, USA.
  5. B. Lewin, “Genes VI”, Oxford University Press.